Rows: 28,843
Columns: 25
$ cas <fct> Piura, Piura, Cusco, Cusco, Cusco, Cusco, Cusco, Cusco, Cu…
$ sex <fct> Femenino, Masculino, Femenino, Femenino, Masculino, Femeni…
$ age <dbl> 99, 100, 99, 99, 99, 99, 99, 99, 99, 100, 99, 99, 99, 96, …
$ hta <fct> 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0…
$ dm <fct> 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1…
$ crea <dbl> 1.00, 1.03, 0.96, 1.13, 1.31, 0.91, 0.98, 1.37, 1.30, 1.15…
$ ckd_stage2 <fct> Stages 1-3 y 5, Stages 1-3 y 5, Stages 1-3 y 5, Stages 3b-…
$ eGFR_ckdepi <dbl> 46.67256, 59.33391, 49.03382, 40.26148, 44.67792, 52.30950…
$ acr <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ urine_album <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ urine_crea <dbl> NA, 120.87, NA, 62.80, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
$ time5y <dbl> 5.000000, 5.000000, 5.000000, 5.000000, 5.000000, 5.000000…
$ eventd5y <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 2, 0, 2…
$ grf_cat <fct> G3a, G3a, G3a, G3b, G3b, G3a, G3a, G3b, G3a, G3a, G3a, G3a…
$ acr_cat <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ ckd_class <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ death2y <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0…
$ eventd2ylab <fct> Alive w/o Kidney Failure, Alive w/o Kidney Failure, Alive …
$ death5y <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1…
$ eventd5ylab <fct> Alive w/o Kidney Failure, Alive w/o Kidney Failure, Alive …
$ eventd <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 2, 0, 2…
$ time <dbl> 9.993155, 9.563313, 9.982204, 8.974675, 8.974675, 8.974675…
$ cas2 <fct> Otras Redes, Otras Redes, Otras Redes, Otras Redes, Otras …
$ cumhaz1 <dbl> 0.06149899, 0.06149899, 0.06149899, 0.06034024, 0.06034024…
$ cumhaz2 <dbl> 0.54808445, 0.51587330, 0.54808445, 0.47474466, 0.47474466…